Data

Tools

Indexes

Applications

Experiments

Open Source Science

quantum-tlcm

This repository contains Python code and data files for solving the Two-Level Crossing Minimization Problem using a D-Wave hybrid solver.

https://github.com/s-caro/quantum-tlcm

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: springer.com
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (8.4%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

This repository contains Python code and data files for solving the Two-Level Crossing Minimization Problem using a D-Wave hybrid solver.

Basic Info
  • Host: GitHub
  • Owner: s-caro
  • Language: Python
  • Default Branch: main
  • Size: 79.1 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Citation

README.md

Quantum-TLCM

Authored by: - Susanna Caroppo - Giordano Da Lozzo - Giuseppe Di Battista

This repository contains the code and data used for the experiments presented in the paper "Quantum Graph Drawing", which was accepted at WALCOM 2024. The experiments focus on solving the Two-Level Crossing Minimization Problem using a D-Wave hybrid solver.

Contents

  • experimental_dataset.txt: Contains the datasets used in the experiments.
  • Two_Layer_Crossing_Minimization.py: Contains the scripts and source code to run the experiments.

Requirements

To run the code in this repository, you will need:

  • D-Wave Ocean SDK
  • Other dependencies listed in requirements.txt

Usage

  1. Clone the repository: bash git clone https://github.com/s-caro/Quantum-TLCM.git cd quantum-graph-drawing

  2. Install the required packages: bash pip install -r requirements.txt

  3. Run the experiments: bash python run_experiments.py

Reproducing the Experiments

To reproduce the experiments as described in the paper, follow the steps outlined in the run_experiments.py script. Detailed instructions and parameters used for each experiment can be found in the script comments.

Contact

For any questions or issues, please contact:

  • Susanna Caroppo - susanna.caroppo@uniroma3.it

Owner

  • Name: Sue
  • Login: s-caro
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Caroppo"
  given-names: "Susanna"
  orcid: "https://orcid.org/0009-0001-4538-8198"
- family-names: "Di Battista"
  given-names: "Giuseppe"
  orcid: "https://orcid.org/0000-0003-4224-1550"
- family-names: "Da Lozzo"
  given-names: "Giordano"
  orcid: "https://orcid.org/0000-0003-2396-5174"
title: "Quantum Graph Drawing"
version: 2.0.4
doi: https://doi.org/10.1007/978-981-97-0566-5_4
date-released: 2024-02-29
url: "https://github.com/s-caro/Quantum-TLCM"

GitHub Events

Total
Last Year

Dependencies

requirements.txt pypi
  • dimod *
  • dwave-ocean-sdk *
  • jsonlib-python3 *
  • matplotlib *
  • networkx *